How to Leverage Constantly Evolving Fleet Analytics

With the sheer volume of data available to fleet managers today, it’s easy to get overwhelmed.

But, don’t take shortcuts and simply ignore the data being generated by your fleet operation. By taking steps to ensure data is being properly gathered and analyzed, creating action items to increase cost savings has never been easier.

Several fleet management company subject-matter experts shared their advice for fleet managers looking to better leverage this growing aspect of fleet management.

Growing Importance of Analytics

When reviewing analytics, abundant and accurate data is king. Successfully managing and improving a fleet’s performance requires multiple levels of data across a vehicle’s lifecycle, and tying that data together is key to getting the big picture.

“Access to data has improved significantly in the past several years, from onboard vehicle telematics to fleet-cost data granularity. Integration of all data sources has led to a greater ability to manage fleet operations and costs. At the same time, large volumes of data can result in hours of analysis with no real return in the way of fleet operational and cost optimization. Data and analytical models should align with corporate fleet goals and provide measurable and meaningful results,” said Jeff Hurrell, regional sales manager – Western Region for Union Leasing.

At A Glance

When looking to leverage the abundance of available fleet analytics, follow these main steps:

Determine what data is needed and avoid "analysis paralysis."

Gather the data into a user friendly format.

Assemble a team to review and analyze the data.

Ask pertinent questions to create actionable items.

“Fleet’s ‘Big Data’ push continues to grow as more data is integrated across the lifecycle of the vehicle. The data offers incremental opportunities for improvement if it is integrated and actionable,” said Dan Hannan, executive director of strategic consulting for Merchants Fleet Management.And, today, there is more information available at a fleet manager’s fingertips than ever before.

Additionally, technology continues to play a role in the improvement of analytical data.

“Telematics is improving the data quality of current key fleet metrics as well as increasing the metrics available for aiding decision making,” said Amy Blaine, VP – Consulting, Analytics and Sustainability for Donlen. “For example, odometer reading is a key metric used to drive many fleet decisions. This data is currently captured through a variety of processes and the data captured is subject to multiple errors leading to poor decisions or wasted time chasing down the correct information. Once this information is available automatically, fleet managers can spend more time on quality decision making, rather than data quality issues.”

And, with data comes knowledge, which can be translated into actionable items to make a lasting change with a fleet operation.

“There is real power in data, which can serve as the catalyst for introducing significant and positive change throughout a fleet. But, analytics involves more than just having the data. Fleet managers must ensure they understand what the data is telling them, which means they need systems in place to make sense of it all,” said Don Woods, department head, Client Information Systems (CIS) for ARI. “Meaningful action and genuine cost savings can only be uncovered once you have the ability to not just see the data, but understand it as well.”

There are many areas that can be improved on through properly gathering and analyzing fleet data.

In the end, taking the data and creating an action plan, or strategy for improvement, is important.

“Data should allow fleet managers to create a tailored fleet strategy to gain control of their overall expenses, driving down costs. The analytics should paint a clear picture that identifies strategies to best lower total operating costs, including acquisition strategy, maintenance, fuel, etc.,” said Terri Wallace, VP of the Client Experience for Mike Albert Fleet Solutions.

Avoiding Data Overload

The main component in leveraging fleet analytics is assembling and analyzing actual fleet data. Once that has been done, the second step is sorting through and evaluating all of that data to look at the information that matters most to a company’s fleet.

With the amount of information available on just about every component of a vehicle’s use, operation, and overall lifecycle, it’s important that fleet managers invest time in the data evaluation process.

“Either the current direction will be confirmed or an opportunity can be explored. This often starts with reviewing something that has ‘always been done that way,’ ” said Brad Jacobs, director of strategic consulting for Merchants Fleet Management.

And, it’s well known that fleet is complicated, resulting in an overwhelming amount of data.

“This can cause analysis paralysis, where so much data is available, the fleet manager doesn’t know where to start or what action to take and how. Making educated and proactive decisions regarding your fleet program can ensure you have a positive impact on your overall business goals,” said Wallace of Mike Albert Fleet Solutions.

“Asking for everything with the hopes of finding the ‘needle in the haystack’ is all too common,” Michno said.

Also, one step to curb data overload is to simply ensure the data accumulated is the data actually needed.

“Decide on an appropriate set of key performance indicators (KPIs) to use to manage the fleet, such as cost per mile for the overall fleet and/or by major category of spend, fuel efficiency (mpg), order-to-delivery times for new orders, and days to sell for remarketed vehicles being some popular KPIs,” said Blaine of Donlen.

In the end, just breathe.

“Just take it one step at a time and don’t get overwhelmed by the volume of data that’s available to fleet managers today,” Blaine noted.

Assembling the Numbers

There isn’t one piece of data or action item alone that affects a fleet manager’s ability to leverage fleet analytics.

“Success involves a combination of things: You need to pick the right partners, invest in a platform that is both flexible and accessible, consider the scalability and sustainability of your approach, utilize your existing supply chain relationships, and research best practices,” said Woods of ARI.

One good place to start leveraging analytical data is to understand your organization’s business and fleet goals.

“Every company has a strategy, goals, and objectives. Make sure that what you are tracking and analyzing supports those goals. Determine what is most important to your particular business strategy and current objectives, and allow that to drive the metrics you will track,” said Michno of Element Fleet Management.

Being able to meet these goals through the use of measurable analytics is the objective.

“Analytical data broken down into specific cost categories should be evaluated against individual fleet trends and industry benchmarks. Financial performance exceptions should be evaluated for significance and the ability of the fleet manager to influence those metrics,” said Hurrell of Union Leasing.

Remember, each fleet is different and there is not always a “one-size-fits-all” approach.

“For some fleets, such as pharmaceutical sales fleets, the vehicle is frequently considered part of the compensation package, so incentivizing the driver by vehicle selection can be a key goal; however, for service-oriented fleets, such as those in the telecommunications industry, each vehicle on the road is generating revenue and finding replacement units due to customized configurations can be difficult, so minimizing downtime is an important goal for these fleets,” said Blaine of Donlen.

Once you understand your organization’s business and fleet goals, it’s time to start asking questions.

“When undertaking analytics, fleet managers should vet the driving questions with relevant stakeholders. Efforts should be centralized around pertinent questions with actionable results. Also, analytics will only be as accurate as the data used. The team should ensure the data is a true representation of the full space and that it has been adequately ‘scrubbed’ for quality,” said Candace Trautwein, senior data analyst for GE Capital Fleet Services.

And, to ask the right questions, a strong fleet manager must have a good grasp on any current or potential problems.

“The importance of analytics is critical to identifying data anomalies. Fleet managers should be looking for data that not only points to a problem, but also identifies solutions as well. In the volatile market, fleet managers should be seeking real-time responses, not just casual analysis. Utilizing expanding data sets and historical trending patterns, predictive modeling has become the primary form of analytics to drive down costs,” said Mark Donahue Jr., manager – fleet analytics for EMKAY.

Finally, ensure all questions being asked are pertinent, actionable items.

“Challenge your team to quantify savings opportunities and include an action plan when delivering the results of the analysis. Finally, when implementing any actions, develop a plan to track or measure success,” said Lucas Kinzel, senior data analyst for GE Capital Fleet Services.

Also, understand how to make change happen within your company so that action can happen.

“Fleet managers need to understand the ‘levers’ that directly, or indirectly, impact a company’s cost-savings objectives. Cost savings can be influenced by many factors, including fleet policy, operational efficiencies, fleet vehicle strategies, and corporate culture relative to vehicle usage,” said Hurrell of Union Leasing.

Once an organization’s priorities and goals are understood and pertinent questions are noted, the next step is to assemble an analytical team.

“Analytics are most effective when technical and statistical know-how is paired with industry experience. As such, the best way to make use of analytics is to have the right team working on these investigations. It is also important to use analytics and IT resources wisely,” Kinzel said.

TOP MISTAKES TO AVOID WHEN GATHERING DATA

When leveraging fleet analytics, there are more than a few mistakes fleet managers can make. Fleet management company subject-matter experts shared the top mistakes they see being made in data gathering:

Ignoring the context in relation to different fleet vehicles, such as light-vs. heavy-duty trucks, including seasonality and replacement cycles.

Asking and researching the wrong questions. Ensure all questions are focused inquiries that are relevant to the business and provide the best cost / benefit results. The results of your analysis are only as good as the data upon which they are based.

Using too small of a sample size. Looking at a larger data sample better allows for a finite slicing and dicing of data and helps avoid data skewed by incidental occurences.

Not ensuring high-quality data. Data quality checks are critical to ensuring that predictive and historical models are robust.

Trying to develop a data model that accounts for everything.

Analyzing the Data

According to Michno of Element Fleet Management, fleet managers and data analysts tend to forget an oft-repeated adage: Correlation does not mean causation.

“A relationship between two trends does not mean that one affects the other. It is important to keep an open mind and consider all possible reasons for a trend,” said Michno of Element Fleet Management.

Trautwein of GE Capital Fleet Services agreed. “Pure IT or statistical teams will find many correlations, but without the ability of a fleet professional to interpret the findings incorrect conclusions may be reached,” she said.

Once an organization’s priorities are clearly understood and a team is assembled, the next step to analyzing fleet data from a total cost of ownership perspective is ensuring the availability of comprehensive data.

“For example, making vehicle selection decisions by minimizing acquisition costs while not considering operational costs or resale value can lead to sub-optimal decisions,” said Blaine of Donlen.

Access to meaningful data is important to help understand the story data can tell.

“Fleet managers can utilize the data to not only drive down costs, but also to compare how their fleet may match up or benchmark against other fleets,” said Wallace of Mike Albert Fleet Solutions.

In the end, better data leads to better decisions.

“Fleet program costs are driven by a series of decisions concerning the fleet operations. The use of ‘Big Data’ analysis allows fleet managers to access information and models around these decisions not possible in the past. For example, in a total cost of ownership analysis, we are able to pull together millions of records to create more accurate maintenance forecasts than ever before,” said James Thompson, strategic consulting & analytics manager for GE Capital Fleet Services.

And, don’t forget the importance of relationships in any business matter.

Once data is assembled and priorities are understood, to truly drive down costs through leveraging analytical data, fleet managers must first find a starting point.

“Create a baseline based on historical data and focus on behavioral and cost items (such as speeding, idling, driver patterns, and vehicle cycles). Model the optimal solution based on actual data for a given vehicle and create an ongoing plan to manage the strategy,” said Jacobs of Merchants Fleet Management.

Looking back at a fleet’s historical data is a strong starting point for future measurements.

“A historical trend analysis can offer actionable fleet program cost-savings opportunities when evaluated through meaningful metrics. Fleet management billing data, while offering a high-level view of cost trends, does not necessarily offer the appropriate insight into fleet performance without integrated into the correct metric. For instance, when evaluating fuel spend year-over-year, an increase in fuel spend may not be significant when viewed as total spend. Many factors influence total spend including total miles driven, fleet vehicle mix, fuel cost per gallon, and total fleet count,” said Hurrell of Union Leasing.

Also, take a look at model- and mileage-specific depreciation break-even periods to determine if fleet is over-amortizing its vehicle assets.

“When a fleet is consistently receiving large gains at sale on their remarketed vehicles, the fleet manager should review options to adjust their amortization periods to reduce these gains at sale and obtain a cash flow benefit for their organization. A depreciation break-even analysis will assist fleet managers with finding a comfortable amortization rate that coincides with their fleet’s replacement parameters,” said Becky Langmandel, director, Strategic Modeling and Analytics Research for LeasePlan USA.

Reviewing replacement cycles to ensure optimal vehicle use is another way that analytical data can be utilized to ensure vehicles are run at the lowest possible cost per mile.

“Fleet managers often replace vehicles too early — or too late — in the lifecycle, which drives up the average monthly depreciation expense. By requesting a fleet-specific optimum replacement analysis and adjusting the fleet’s replacement parameters, fleet managers are better able to optimize the life of their vehicles,” Langmandel continued.

Finally, one important area not to forget about when analyzing fleet analytical data is exception reporting.

“Monitor exception reports at the vehicle level to identify savings opportunities such as low fuel-efficiency vehicles, which could be an indicator of poor odometer data typically captured by fueling transactions at the pump, or inefficient driving, both of which could be handled by coaching drivers,” said Blaine of Donlen.

Follow up on the exception reports pulled when analyzing the data to make changes happen.

“Follow up on exceptions to control day-to-day costs and let the field know how they are expected to participate in the process to help control costs,” Blaine continued.

Taking Action

Once data has been assembled and analyzed, fleet managers must next take action, with an overall goal of driving down costs.

And, according to Woods of ARI, not much has changed in terms of the main fleet cost drivers.

“The primary factors that affect direct fleet costs have not changed all that much over the last 20 years, and the biggest drivers remain vehicle procurement, maintenance expenditures, fuel costs and mpg, and driver abuse (including accident damage),” he said. “As vehicles have become more reliable, however, fleet managers have started to consider indirect factors that can affect costs as well, including such items as vehicle availability (e.g. downtime management) and rightsizing.”

In this environment, according to Woods, “the best way for a fleet manager to use analytical data is to use it to gain insight into how a fleet may be operating, determine what factors may be affecting costs, and seek to uncover possible efficiency improvements and cost savings.”

Additionally, today’s fleet managers today have a number of available options when leveraging data for cost-saving opportunities.

Work with key stakeholders to create an action plan tailored to the data’s results and your fleet’s specific needs.

“The data assembled should allow fleet managers to create a tailored strategy to gain control of their overall expenses, thus driving down costs. The analytics should paint a clear picture that identifies strategies to best lower total operating costs, including acquisition strategy, maintenance, fuel, etc.,” said Wallace of Mike Albert Fleet Solutions.

Also, consider predictive modeling, which, according to Donahue of EMKAY, is among the most advanced analytics methods.

“It entails performing data analysis to identify patterns and outliers to make predictions about potential future events. This form of analysis provides insights into various activities. Examples include forecasting fuel prices based upon volatile market conditions, identifying catastrophic failures at particular mileage parameters, and identifying the best time to remarket fleet vehicles based upon seasonality and historical trends,” Donahue said.

Top Mistakes to Avoid when Analyzing Data

Fleet management company subject-matter experts shared the top mistakes they see being made in analyzing data:

Analysis paralysis: Getting overwhelmed by the volume of data, and choosing to ignore it as a result.

Not evaluating data from a holistic approach and understanding opportunities for cost savings.

Not understanding how the fleet is performing against peer benchmarks. Do not look at fleet data in a “vacuum,” fleet managers must look at the global view with their industry benchmarks.

Improperly segmenting data and drawing incorrect conclusions.

Ignoring variances, anomalies, and outliers. An average doesn’t always tell the whole story.

Not understanding the details or formulas used to understand the origin of the numbers in order to make more informed decisions.

Believing that a pattern proves cause and effect; fleet managers must consider all variables and how they influence one another.

Relying only on the numbers.

Making decisions based on incomplete data, e.g., only examining acquisition costs and ignoring operational costs.

Buying into the concept that a fully depreciated unit is a “free car.”

The Bottom Line

An important item to keep in mind, according to Michno of Element Fleet Management, is that all of the benefits of fleet analytics could disappear if an organization is not ready to act on the recommendations.

“It is crucial to get buy-in from upper management and make the best use of data,” said Michno of Element Fleet Management. “Also, know what success looks like — understand how metrics will be interpreted and have achievable goals in sight.

Remember, data will help in making informed decisions. “Data provides fleet managers with the knowledge to make the right decisions, or, at least put more certainty into a decision. This will be crucial in obtaining support from upper management and influencing change,” Michno said.

Once fleet analytics are pulled, don’t stop there.

“Fleet managers should continue to remain focused on key metrics and cost trends that have been effective in the past to manage fleet costs. Endless streams of data and numerous graphical views can create a confusing environment without necessarily producing actionable strategies. As new data points evolve, careful consideration should be placed on how this data should be used,” said Hurrell of Union Leasing.

And, in the end, it’s all just numbers if no one does anything with the information.

“Data and numbers unto themselves don’t tell enough of a story to drive any cost or productivity enhancements. It is only when a fleet manager is able to interpret the information and see how the different data points correlate that the real value becomes evident. As systems and technologies continue to evolve and models become more prescriptive in nature, both outcomes will be able to be better predicted, and responses to those outcomes can be preemptively recommended,” said Woods of ARI.

Reports are powerful, but not will not have a strong and lasting impact if an organization is not having a dialogue about the data. It is what is done with the data that is going to have the most impact.

“It is essential to understand that, for fleet analytics to have impact, one must measure, monitor, predict, and change. Analytics is the future of everything,” said Donahue of EMKAY.

Remember, there is an abundance of data at your fingertips; you just have to know how to sort through and interpret it all.

“How you use that data to tell a story is what will make a material impact on your business. Fleet is complicated and, while fleet managers can be trained to look at their own data, without comparative insights and benchmarks, they may be working toward the wrong goals and not achieve the desired results,” said Wallace of Mike Albert Fleet Solutions.

Top Mistakes to Avoid when Taking Action On Analytics

Fleet management company subject-matter experts shared the top mistakes they see being made in taking all of the data gathered and analyzing and taking action on it to realize cost savings:

Getting “hung up” on data that is not actionable.

Not factoring in all core areas of spend that can be controlled, or attempting to execute a solution before understanding the data.

Not putting results into the right context when interpreting data.

Not following through on corrective, preventive, or alternative actions. If fleet managers ignore the data and don’t act on results, it could cost a company millions.